Abstract-Since traffic diversity and volume increase with growing popularity of mobile applications, there is the strong need to manage the traffic carried by networks. Software defined networks can simplify network management while enabling new services by employing traffic management including routing whose goal is to maximize the given utility while satisfying capacity requirements. In this paper, we propose an efficient routing algorithm to minimize the cost based on power consumption determined by the number of active OpenFlow switches in a software defined network while satisfying throughput requirements of all flows according to constraints on link capacities in the network. We evaluate the performance of the proposed algorithm based on the number of active switches for different network topologies with various scenarios.
The need for software defined mobile networking (SDMN) increases to manage the complexity in communication networks for the fifth generation mobile networks and beyond, with increasing diverse demand on data traffic in wireless environments. The separation of the data and control planes offers flexibility in future networks with SDMN by taking into account to the wireless access problem in complex radio environments. In this paper, we propose an efficient joint routing and resource allocation algorithm to minimize the cost based on power consumption while satisfying both throughput and delay requirement of the flows under a given capacity of links in night time traffic through SDMN. The power consumption is determined based on the number of active OpenFlow switches and active ports in the network. In the proposed joint algorithm, we put the selected network components to sleep mode in order to reduce overall network power consumption. The performances of the proposed algorithm are illustrated under different throughput constraints in various network topologies and scenarios in night-time traffic.
Özetçe -Mobil uygulamaların gittikçe yaygınlaşması ile artan trafik çeşitliligi ve hacmi, aglarda taşınan trafigin yönetilmesi ihtiyacını kuvvetlendirdi. Yazılım tanımlı aglar, trafik yöneti-mini kullanarak belirlenen gereksinimleri karşılarken, verimi maksimuma çıkararak agları yönetebilir. Bu bildiride, agdaki aktif anahtar sayısına dayanan güç tüketimini minimuma indiren bir yol atama algoritması öneriyoruz. Baglantı kapasitesi kısıtlamalarını göz önüne alarak, akışların veri hacmi gereksinimlerini karşılayan en iyi yolu bulmak için genetik algoritma kullanıp, düşük karmaşıklıklı yeni bir yol atama yaklaşımı öner-iyoruz. Önerilen algoritmanın verilen ag topolojisinde çeşitli akış veri hacmi kısıtlamalarına göre performans degerlendirmelerini sunuyoruz.Anahtar Kelimeler-Yazılım tanımlı ag, yol atama, genetik algoritma.Abstract-Since traffic diversity and volume increase with growing popularity of mobile applications, there is the strong need to manage the traffic carried by networks. Software defined networking can manage network while enabling new services by employing traffic management whose goal is to maximize the utility objective while satisfying given requirements. In this paper, we propose an efficient routing to minimize the cost based on power consumption determined by the number of active switches in a software defined networks. An optimum solution obtained by genetic algorithm and a reduced complexity routing approach are proposed while satisfying throughput requirements of flows for given constraints on link capacities in the network. We provide the performance evaluations of the proposed algorithms with respect to different throughput constraints of flows in a given network topology.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.